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Registro Completo |
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Biblioteca(s): |
Embrapa Instrumentação. |
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Data corrente: |
16/11/2021 |
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Data da última atualização: |
09/06/2022 |
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Tipo da produção científica: |
Artigo em Periódico Indexado |
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Autoria: |
FURUYA, D. E. G.; MA, L.; PINHEIRO, M. M. F.; GOMES, F. D. G.; GONÇALVEZ, W. N.; MARCATO JUNIOR, J.; RODRIGUES, D. de C.; BLASSIOLI- MORAES, M. C.; MICHEREFF, M. F. F.; BORGES, M.; ALAUMANN, R. A.; FERREIRA, E. J.; OSCO, L. P.; RAMOS, A. P. M.; LI, J.; JORGE, L. A. de C. |
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Afiliação: |
MARIA CAROLINA BLASSIOLI MORAES, Cenargen; MIGUEL BORGES, Cenargen; EDNALDO JOSE FERREIRA, CNPDIA; LUCIO ANDRE DE CASTRO JORGE, CNPDIA. |
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Título: |
Prediction of insect-herbivory-damage and insect-type attack in maize plants using hyperspectral data. |
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Ano de publicação: |
2021 |
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Fonte/Imprenta: |
International Journal of Applied Earth Observation and Geoinformation, v. 105, 102608, 2021. |
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Páginas: |
1 - 10 |
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ISSN: |
0303-2434 |
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DOI: |
https://doi.org/10.1016/j.jag.2021.102608 |
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Idioma: |
Inglês |
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Conteúdo: |
Accurately detecting the insect damage caused in plants might reduce losses in crop yields. Hyperspectral data is a well-accepted data source to attend this issue. However, due to their high dimensional, both robust and intelligent methods are required to extract information from these datasets. Therefore, we explore the processing of hyperspectral data with artificial intelligence methods joined with clustering techniques to detect insect herbivory damage in maize plants. We measured the leaf spectral response from three different groups of maize plants: control (undamaged plants); damaged by Spodoptera frugiperda herbivory, and damaged by Dichelops meiacanthus. Data were collected with a FieldSpec 3.0 Spectroradiometer from 350 to 2500 nm for eight consecutive days. We adjusted eight machine learning methods. We also determined the most contributive wavelengths to differentiate undamaged from damaged plants by insect herbivore attack using clustering strategy. For that, we applied the clusterization method based on a self-organizing map (SOM). The Random Forest (RF) model is the overall best learner, and up to the 5th day of analysis represents the most adequate day to segregate maize undamaged from damaged maize. RF was able to separate the three groups of treatments with an F1-measure of up to 96.7% (Recall of 96.7% and Precision of 96.7%). Additionally, we found out that the most representative spectral regions are located in the near-infrared range. Our approach consists of an original contribution to early differentiate the undamaged plant from the damaged one due to insect-attack, highlighting the most contributive wavelengths to map this occurrence. MenosAccurately detecting the insect damage caused in plants might reduce losses in crop yields. Hyperspectral data is a well-accepted data source to attend this issue. However, due to their high dimensional, both robust and intelligent methods are required to extract information from these datasets. Therefore, we explore the processing of hyperspectral data with artificial intelligence methods joined with clustering techniques to detect insect herbivory damage in maize plants. We measured the leaf spectral response from three different groups of maize plants: control (undamaged plants); damaged by Spodoptera frugiperda herbivory, and damaged by Dichelops meiacanthus. Data were collected with a FieldSpec 3.0 Spectroradiometer from 350 to 2500 nm for eight consecutive days. We adjusted eight machine learning methods. We also determined the most contributive wavelengths to differentiate undamaged from damaged plants by insect herbivore attack using clustering strategy. For that, we applied the clusterization method based on a self-organizing map (SOM). The Random Forest (RF) model is the overall best learner, and up to the 5th day of analysis represents the most adequate day to segregate maize undamaged from damaged maize. RF was able to separate the three groups of treatments with an F1-measure of up to 96.7% (Recall of 96.7% and Precision of 96.7%). Additionally, we found out that the most representative spectral regions are located in the near-infrared range. Our approach consis... Mostrar Tudo |
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Palavras-Chave: |
Proximal hyperspectral sensing; Random forest. |
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Categoria do assunto: |
-- |
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Marc: |
LEADER 02800naa a2200361 a 4500
001 2136152
005 2022-06-09
008 2021 bl uuuu u00u1 u #d
022 $a0303-2434
024 7 $ahttps://doi.org/10.1016/j.jag.2021.102608$2DOI
100 1 $aFURUYA, D. E. G.
245 $aPrediction of insect-herbivory-damage and insect-type attack in maize plants using hyperspectral data.$h[electronic resource]
260 $c2021
300 $a1 - 10
520 $aAccurately detecting the insect damage caused in plants might reduce losses in crop yields. Hyperspectral data is a well-accepted data source to attend this issue. However, due to their high dimensional, both robust and intelligent methods are required to extract information from these datasets. Therefore, we explore the processing of hyperspectral data with artificial intelligence methods joined with clustering techniques to detect insect herbivory damage in maize plants. We measured the leaf spectral response from three different groups of maize plants: control (undamaged plants); damaged by Spodoptera frugiperda herbivory, and damaged by Dichelops meiacanthus. Data were collected with a FieldSpec 3.0 Spectroradiometer from 350 to 2500 nm for eight consecutive days. We adjusted eight machine learning methods. We also determined the most contributive wavelengths to differentiate undamaged from damaged plants by insect herbivore attack using clustering strategy. For that, we applied the clusterization method based on a self-organizing map (SOM). The Random Forest (RF) model is the overall best learner, and up to the 5th day of analysis represents the most adequate day to segregate maize undamaged from damaged maize. RF was able to separate the three groups of treatments with an F1-measure of up to 96.7% (Recall of 96.7% and Precision of 96.7%). Additionally, we found out that the most representative spectral regions are located in the near-infrared range. Our approach consists of an original contribution to early differentiate the undamaged plant from the damaged one due to insect-attack, highlighting the most contributive wavelengths to map this occurrence.
653 $aProximal hyperspectral sensing
653 $aRandom forest
700 1 $aMA, L.
700 1 $aPINHEIRO, M. M. F.
700 1 $aGOMES, F. D. G.
700 1 $aGONÇALVEZ, W. N.
700 1 $aMARCATO JUNIOR, J.
700 1 $aRODRIGUES, D. de C.
700 1 $aBLASSIOLI- MORAES, M. C.
700 1 $aMICHEREFF, M. F. F.
700 1 $aBORGES, M.
700 1 $aALAUMANN, R. A.
700 1 $aFERREIRA, E. J.
700 1 $aOSCO, L. P.
700 1 $aRAMOS, A. P. M.
700 1 $aLI, J.
700 1 $aJORGE, L. A. de C.
773 $tInternational Journal of Applied Earth Observation and Geoinformation$gv. 105, 102608, 2021.
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Registro original: |
Embrapa Instrumentação (CNPDIA) |
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| Registros recuperados : 12 | |
| 4. |  | PIMENTA-MARTINS, M. G. R.; FURTADO, R. F.; DUTRA, R. F.; HENEINE, L. G. D.; DIAS. R. S.; BORGES, M. de F.; ALVES, C. R. Immunosensor based on ink printed electrode for staphylococcal enterotoxin detection. Revista da Universidade Vale do Rio Verde, Três Corações, v. 12, n. 1, p. 895-904, 2014.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 4 |
| Biblioteca(s): Embrapa Agroindústria Tropical. |
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| 7. | | GRAÇAS, A. V. das; BARBOSA, M. G.; OLIVEIRA, L. K. V. de; SCHIMITZ, A. R.; ANDRÉ, A. L. G.; MARTINS, M. G.; CAMPOS, M. M. Efeitos da suplementação com nitrato de cálcio sobre os parâmetros ruminais de novilhos em recria. In: WORKSHOP DE INICIAÇÃO CIENTÍFICA DA EMBRAPA GADO DE LEITE - PIBIC/CNPq, 31., 2025, Juiz de Fora. Anais [...]. Juiz de Fora: Embrapa Gado de Leite, 2025. p. 51-54. ODS 13.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Gado de Leite. |
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| 8. | | PIMENTA-MARTINS, M. G. R.; FURTADO, R. F.; BORGES, M. de F.; HENEINE, L. G. D.; MATTOSO, L. H. C.; HERRMANN, P. S. de P.; OLIVEIRA, J. E. de; ALVES, C. R. Imunossensor amperométrico para detecção de enterotoxina estafilocócica em queijo. In: WORKSHOP DA REDE DE NANOTECNOLOGIA APLICADA AO AGRONEGÓCIO, 6., 2012, Fortaleza. Anais... São Carlos: Embrapa Instrumentação; Fortaleza: Embrapa Agroindústria Tropical, 2012. p. 76-78. Editores: Maria Alice Martins, MOrsyleide de Freitas Rosa, Men de Sá Moreira de Souza Filho, Nicodemos Moreira dos Santos Junior, Odílio Benedito Garrido de Assis, Caue Ribeiro, Luiz Henrique Capparelli Mattoso.| Tipo: Artigo em Anais de Congresso |
| Biblioteca(s): Embrapa Instrumentação. |
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| 9. | | GRAÇAS, A. V. das; RIBEIRO, E. F.; SILVA, A. L. da; OLIVEIRA, L. K. V. de; FERREIRA, S. E.; MARTINS, M. G.; SILVA, C. S. da; CAMPOS, M. M. Efeitos de suplemento composto por extrato de plantas, óleos essenciais, levedura, vitaminais e minerais sobre os parâmetros ruminais, consumo, atividade e ruminação de vacas Girolando. In: ENCONTRO NACIONAL DA REDE DE PESQUISA E INOVAÇÃO EM SANIDADE E PECUÁRIA LEITEIRA A CRIAÇÃO DE BEZERRAS E SEUS DESAFIOS SANITÁRIOS, 3., 2025, Lavras. Anais do evento. Lavras: Universidade Federal de Lavras, 2025. p. 80. Tema: A criação de bezerras e seus desafios sanitários.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Gado de Leite. |
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| 10. | | SILVA, S. L. D.; CÔRTES, L. R.; MARTINS, A. L.; FREITAS, B. W. de; VIEIRA, S. F.; RANGEL, P. S. C.; MARTINS, M. G.; FONSECA, J. F. da; BRANDÃO, F. Z.; SIQUEIRA, L. G. B. Effects of hCG administered by different routes seven days after onset of estrus in synchronous estrus induced acyclic dairy goats. Animal Reproduction, v. 21, n. 3, p. 110, 2024. Edição dos resumos da 37ª Annual Meeting of the Brazilian Embryo Technology Society, 2024, Atibaia, SP.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Caprinos e Ovinos; Embrapa Gado de Leite. |
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| 11. | | DANTAS, T. V. M.; CUNHA, R. M. S.; TEIXEIRA, M. F. S.; MARTINS, M. G. Q.; PINHEIRO, R. R.; FEITOSA, A. L. V. L.; BRITO, R. L. L.; ARAÚJO, S. A. C.; MELO, V. S. P.; RODRIGUES, A. S.; ANDRIOLI, A. Expression of recombinant P28 protein of the goat caprine arthritis encephalitis virus in Escherichia coli. Virus Reviews and Research, v. 16, supl. 1, p. 230, oct., 2011. Abstract. VV356. Trabalho apresentado no XXII National Meeting of Virology & VI mercosur Meeting of Virology, Atibaia, São Paulo.| Tipo: Resumo em Anais de Congresso |
| Biblioteca(s): Embrapa Caprinos e Ovinos. |
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| 12. | | MARTINS, C. M. do C. R; SÁ, D. R. C. de; MARTINS, M. G.; SOUZA, M. A. S. de; BEZERRA, A. D. da S.; SOUZA, M. R. de; ARAUJO, B. N.; ROSA, D. S.; GOUVEIA, G. V.; COSTA, M. M. da; RODRIGUES, R. T. de S. Multidrug resistance and biofilm-forming ability of Escherichia coli isolated from free-range chicken meat in restaurants in Petrolina, Pernambuco, Brazil. Open Veterinary Journal, v. 16, n. 1, p. 616-625, 2026.| Tipo: Artigo em Periódico Indexado | Circulação/Nível: B - 1 |
| Biblioteca(s): Embrapa Semiárido. |
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| Registros recuperados : 12 | |
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